Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.

BACKGROUND:Pneumonia is the leading cause of death among children and young people (CYP) with severe cerebral palsy (CP). Only a few studies used nomogram for assessing risk factors and the probability of pneumonia. Therefore, we aimed to identify risk factors and devise a nomogram for identifying t...

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Main Authors: Tsu Jen Kuo, Chiao-Lin Hsu, Pei-Hsun Liao, Shih-Ju Huang, Yao-Min Hung, Chun-Hao Yin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2020-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0235069
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spelling doaj-11518e0612e54aa7ab9eb513360e143e2021-03-03T21:55:48ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-01157e023506910.1371/journal.pone.0235069Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.Tsu Jen KuoChiao-Lin HsuPei-Hsun LiaoShih-Ju HuangYao-Min HungChun-Hao YinBACKGROUND:Pneumonia is the leading cause of death among children and young people (CYP) with severe cerebral palsy (CP). Only a few studies used nomogram for assessing risk factors and the probability of pneumonia. Therefore, we aimed to identify risk factors and devise a nomogram for identifying the probability of severe pneumonia in CYP with severe CP. METHODS:This retrospective nationwide population-based cohort study examined CYP with newly diagnosed severe CP before 18 years old between January 1st, 1997 and December 31st, 2013 and followed them up through December 31st, 2013. The primary endpoint was defined as the occurrence of severe pneumonia with ≥ 5 days of hospitalization. Logistic regression analysis was used for determining demographic factors and comorbidities associated with severe pneumonia. These factors were assigned integer points to create a scoring system to identify children at high risk for severe pneumonia. RESULTS:Among 6,356 CYP with newly diagnosed severe CP, 2,135 (33.59%) had severe pneumonia. Multivariable logistic regression analysis revealed that seven independent predictive factors, namely age <3 years, male sex, and comorbidities of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications. A nomogram was devised by employing these seven significant predictive factors. The prediction model presented favorable discrimination performance. CONCLUSIONS:The nomogram revealed that age, male sex, history of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications were potential risk factors for severe pneumonia among CYP with severe CP.https://doi.org/10.1371/journal.pone.0235069
collection DOAJ
language English
format Article
sources DOAJ
author Tsu Jen Kuo
Chiao-Lin Hsu
Pei-Hsun Liao
Shih-Ju Huang
Yao-Min Hung
Chun-Hao Yin
spellingShingle Tsu Jen Kuo
Chiao-Lin Hsu
Pei-Hsun Liao
Shih-Ju Huang
Yao-Min Hung
Chun-Hao Yin
Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
PLoS ONE
author_facet Tsu Jen Kuo
Chiao-Lin Hsu
Pei-Hsun Liao
Shih-Ju Huang
Yao-Min Hung
Chun-Hao Yin
author_sort Tsu Jen Kuo
title Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
title_short Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
title_full Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
title_fullStr Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
title_full_unstemmed Nomogram for pneumonia prediction among children and young people with cerebral palsy: A population-based cohort study.
title_sort nomogram for pneumonia prediction among children and young people with cerebral palsy: a population-based cohort study.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2020-01-01
description BACKGROUND:Pneumonia is the leading cause of death among children and young people (CYP) with severe cerebral palsy (CP). Only a few studies used nomogram for assessing risk factors and the probability of pneumonia. Therefore, we aimed to identify risk factors and devise a nomogram for identifying the probability of severe pneumonia in CYP with severe CP. METHODS:This retrospective nationwide population-based cohort study examined CYP with newly diagnosed severe CP before 18 years old between January 1st, 1997 and December 31st, 2013 and followed them up through December 31st, 2013. The primary endpoint was defined as the occurrence of severe pneumonia with ≥ 5 days of hospitalization. Logistic regression analysis was used for determining demographic factors and comorbidities associated with severe pneumonia. These factors were assigned integer points to create a scoring system to identify children at high risk for severe pneumonia. RESULTS:Among 6,356 CYP with newly diagnosed severe CP, 2,135 (33.59%) had severe pneumonia. Multivariable logistic regression analysis revealed that seven independent predictive factors, namely age <3 years, male sex, and comorbidities of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications. A nomogram was devised by employing these seven significant predictive factors. The prediction model presented favorable discrimination performance. CONCLUSIONS:The nomogram revealed that age, male sex, history of pressure ulcer, gastroesophageal reflux, asthma, seizures, and perinatal complications were potential risk factors for severe pneumonia among CYP with severe CP.
url https://doi.org/10.1371/journal.pone.0235069
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